Trinocular stereovision by generalized Hough transform

In this paper, we present the generalized Hough transform to match the edge segments in trinocular stereovision. We show that the corresponding segment triplet candidates can be detected by a generalized Hough transform in the parameter space ((theta) ,(phi) ) which characterizes the 3D segment orientation. These triplets can then be verified, and the position parameters of the 3D segments can be detected by a generalized Hough transform in the parameter space (Y,Z). So the matching of geometric primitives in trinocular stereovision images can be found by the cascade of two generalized Hough transforms in the spaces of only two dimensions. Experimental results are reported also. Our method shows the following advantages: (1) Trinocular stereovision image matching is transformed into Hough transforms in 2D parameter spaces, which reduces much the computational complexity. (2) Matching can be done completely in parallel. (3) No a priori similarity between images is needed, so very different views can be used, which improves the precision of 3D reconstruction. (4) It is very efficient to solve false targets. (5) Our method gives good results even for partially hidden segments.